In benchmarks like ALFRED, a PDDL [1]} planner can be used to determine what actions are necessary to solve relatively simple tasks.
In VLN, simple search algorithms yield the shortest paths to goals.
Consequently, some language-guided visual task models build a semantic representation of the environment, then learn a hierarchical policy to execute such planner-style goals [2]}.
